As the Internet technology develops, there are increasingly abundant structural types of information data on the Internet, and how to efficiently acquire key information from a large number of web pages of different structural data types has become an important direction in research.
Usually, an image-text block having images and texts on a web page contains the key information of the web page, for example product information, processing technology, and other key information on the website of a machining equipment manufacturer, and is usually displayed using images and texts. When retrieving an image-text block from a web page, the existing method is generally manually analyzing the HyperText Markup Language (HTML) structure of a page, and obtaining the path of the image-text block by manual annotation, or retrieving the path of page elements of the image-text block clicked by the annotator using an annotation plugin. This method needs to manually annotate each page separately, and has low annotation efficiency. The page structure will be dynamically updated, that is, the HTML structure of the page will change, and it is necessary to reannotate the path of the image-text block, resulting in the inability to implement an automatic update.